ADAS Data & Analytics Engineer

Role Overview

We are looking for a Data & Analytics Engineer with 4–7 years of experience to work on ADAS validation, data processing, and analytics workflows. The role involves handling large-scale vehicle data, building automation pipelines, and generating insights to support decision-making.

Key Responsibilities

Data Processing & Analysis

• Work with ADAS/event-based datasets from multiple sources, including signals, logs, and video-derived data.
• Perform data extraction, cleaning, and transformation using Python.
• Analyze time-series data and derive meaningful insights for validation use cases.

Automation & Workflow Development

• Develop scripts and workflows for automated data processing and reporting.
• Identify opportunities to automate repetitive analytics tasks using ML or rule-based logic.
• Work with orchestration tools such as Airflow, Flyte, or similar tools for pipeline execution.

Data Engineering & Cloud

• Handle large datasets such as Parquet and optimize data pipelines for performance.
• Work with cloud platforms, preferably GCP or AWS, for data storage and processing.
• Integrate APIs and databases for data access and processing.

Visualization & Reporting

• Build dashboards using Power BI, Tableau, or similar tools.
• Design KPIs and visualize insights for stakeholders.
• Ensure clear and structured storytelling of data insights.

Collaboration & Domain Work

• Work closely with validation teams and SMEs to understand data requirements.
• Support ADAS function analysis and validation workflows.
• Contribute to continuous improvement of analytics use cases.

Required Skills

Technical Skills

• Strong Python skills, including Pandas, NumPy, and data processing.
• Good SQL knowledge, including RDBMS and NoSQL basics.
• Experience with large-scale data handling and processing.
• Exposure to cloud environments, preferably GCP or AWS.
• Knowledge of dashboarding tools such as Power BI, Grafana, or Tableau.

Good to Have

• Experience in the ADAS or automotive domain.
• Understanding of time-series data and signal processing.
• Exposure to ML basics, including classification and model usage.
• Knowledge of containerization using Docker or Kubernetes.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Electronics, or a related field.
• 4–7 years of relevant experience in Data Analytics or Data Engineering.

Behavioral Expectations

• Strong analytical and problem-solving skills.
• Ability to work in a dynamic environment.
• Good collaboration and communication skills.
• Structured thinking and ownership mindset.

Benefits

• Employee discounts
• Possible health benefits
• Mobile phone for employees
• Possible meal discounts
• Company retirement plan
• Possible hybrid work
• Mobility offers
• Employee events
• Coaching
• Possible flextime
• Parking
• In-house doctor
• Good public transport
• Barrier-free workplace
• Near-site childcare
• Canteen and café

Contact

Mercedes-Benz Research and Development India Private Limited
Brigade Tech Gardens, Katha No. 119560037
Bengaluru

Dipti Nayak
E-mail: dipti.nayak@mercedes-benz.com